Search Results for author: Guokun Lai

Found 13 papers, 7 papers with code

A Self-enhancement Approach for Domain-specific Chatbot Training via Knowledge Mining and Digest

no code implementations17 Nov 2023 Ruohong Zhang, Luyu Gao, Chen Zheng, Zhen Fan, Guokun Lai, Zheng Zhang, Fangzhou Ai, Yiming Yang, Hongxia Yang

This paper introduces a novel approach to enhance LLMs by effectively extracting the relevant knowledge from domain-specific textual sources, and the adaptive training of a chatbot with domain-specific inquiries.

Chatbot Text Generation

Unsupervised Parallel Corpus Mining on Web Data

no code implementations18 Sep 2020 Guokun Lai, Zihang Dai, Yiming Yang

In contrast, there is a large-scale of parallel corpus created by humans on the Internet.

Machine Translation Parallel Corpus Mining +2

Funnel-Transformer: Filtering out Sequential Redundancy for Efficient Language Processing

3 code implementations NeurIPS 2020 Zihang Dai, Guokun Lai, Yiming Yang, Quoc V. Le

With the success of language pretraining, it is highly desirable to develop more efficient architectures of good scalability that can exploit the abundant unlabeled data at a lower cost.

Reading Comprehension Text Classification

Bridging the domain gap in cross-lingual document classification

1 code implementation16 Sep 2019 Guokun Lai, Barlas Oguz, Yiming Yang, Veselin Stoyanov

We consider the setting of semi-supervised cross-lingual understanding, where labeled data is available in a source language (English), but only unlabeled data is available in the target language.

Classification Cross-Domain Document Classification +7

Re-examination of the Role of Latent Variables in Sequence Modeling

1 code implementation NeurIPS 2019 Zihang Dai, Guokun Lai, Yiming Yang, Shinjae Yoo

With latent variables, stochastic recurrent models have achieved state-of-the-art performance in modeling sound-wave sequence.

Density Estimation

Stochastic WaveNet: A Generative Latent Variable Model for Sequential Data

1 code implementation15 Jun 2018 Guokun Lai, Bohan Li, Guoqing Zheng, Yiming Yang

In this paper, we combine the ideas from both stochastic latent variables and dilated convolutions, and propose a new architecture to model sequential data, termed as Stochastic WaveNet, where stochastic latent variables are injected into the WaveNet structure.

Large-scale Cloze Test Dataset Designed by Teachers

no code implementations ICLR 2018 Qizhe Xie, Guokun Lai, Zihang Dai, Eduard Hovy

Cloze test is widely adopted in language exams to evaluate students' language proficiency.

Cloze Test

Learning Graph Convolution Filters from Data Manifold

no code implementations ICLR 2018 Guokun Lai, Hanxiao Liu, Yiming Yang

Convolution Neural Network (CNN) has gained tremendous success in computer vision tasks with its outstanding ability to capture the local latent features.

Learning Depthwise Separable Graph Convolution from Data Manifold

no code implementations31 Oct 2017 Guokun Lai, Hanxiao Liu, Yiming Yang

Convolution Neural Network (CNN) has gained tremendous success in computer vision tasks with its outstanding ability to capture the local latent features.

Computational Efficiency

Modeling Long- and Short-Term Temporal Patterns with Deep Neural Networks

19 code implementations21 Mar 2017 Guokun Lai, Wei-Cheng Chang, Yiming Yang, Hanxiao Liu

Multivariate time series forecasting is an important machine learning problem across many domains, including predictions of solar plant energy output, electricity consumption, and traffic jam situation.

Multivariate Time Series Forecasting Time Series +1

Cannot find the paper you are looking for? You can Submit a new open access paper.